82 lines
2.5 KiB
C++
82 lines
2.5 KiB
C++
/*
|
|
The Evolving Distribution Objects framework (EDO) is a template-based,
|
|
ANSI-C++ evolutionary computation library which helps you to write your
|
|
own estimation of distribution algorithms.
|
|
|
|
This library is free software; you can redistribute it and/or
|
|
modify it under the terms of the GNU Lesser General Public
|
|
License as published by the Free Software Foundation; either
|
|
version 2.1 of the License, or (at your option) any later version.
|
|
|
|
This library is distributed in the hope that it will be useful,
|
|
but WITHOUT ANY WARRANTY; without even the implied warranty of
|
|
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
|
|
Lesser General Public License for more details.
|
|
|
|
You should have received a copy of the GNU Lesser General Public
|
|
License along with this library; if not, write to the Free Software
|
|
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
|
|
|
|
Copyright (C) 2010 Thales group
|
|
*/
|
|
/*
|
|
Authors:
|
|
Johann Dréo <johann.dreo@thalesgroup.com>
|
|
Caner Candan <caner.candan@thalesgroup.com>
|
|
*/
|
|
|
|
#ifndef _edoSamplerUniform_h
|
|
#define _edoSamplerUniform_h
|
|
|
|
#include <utils/eoRNG.h>
|
|
|
|
#include "edoSampler.h"
|
|
#include "edoUniform.h"
|
|
|
|
/**
|
|
* This class uses the Uniform distribution parameters (bounds) to return
|
|
* a random position used for population sampling.
|
|
*
|
|
* Returns a random number in [min,max[ for each variable defined by the given
|
|
* distribution.
|
|
*
|
|
* Note: if the distribution given at call defines a min==max for one of the
|
|
* variable, the result will be the same number.
|
|
*
|
|
* @ingroup Samplers
|
|
*/
|
|
template < typename EOT, class D = edoUniform<EOT> >
|
|
class edoSamplerUniform : public edoSampler< D >
|
|
{
|
|
public:
|
|
typedef D Distrib;
|
|
|
|
edoSamplerUniform( edoRepairer<EOT> & repairer ) : edoSampler< D >( repairer) {}
|
|
|
|
EOT sample( edoUniform< EOT >& distrib )
|
|
{
|
|
unsigned int size = distrib.size();
|
|
assert(size > 0);
|
|
|
|
// Point we want to sample to get higher a set of points
|
|
// (coordinates in n dimension)
|
|
// x = {x1, x2, ..., xn}
|
|
EOT solution;
|
|
|
|
// Sampling all dimensions
|
|
for (unsigned int i = 0; i < size; ++i)
|
|
{
|
|
double min = distrib.min()[i];
|
|
double max = distrib.max()[i];
|
|
double random = rng.uniform(min, max);
|
|
|
|
assert( ( min == random && random == max ) || ( min <= random && random < max) ); // random in [ min, max [
|
|
|
|
solution.push_back(random);
|
|
}
|
|
|
|
return solution;
|
|
}
|
|
};
|
|
|
|
#endif // !_edoSamplerUniform_h
|